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dc.contributor.authorJanakaraj, Prabhu
dc.contributor.authorWang, Pu
dc.contributor.authorChen, Zheng
dc.date.accessioned2017-01-28T17:37:35Z
dc.date.available2017-01-28T17:37:35Z
dc.date.issued2016
dc.identifier.citationP. Janakaraj, P. Wang and Z. Chen, "Towards Cloud-Based Crowd-Augmented Spectrum Mapping for Dynamic Spectrum Access," 2016 25th International Conference on Computer Communication and Networks (ICCCN), Waikoloa, HI, 2016, pp. 1-7en_US
dc.identifier.isbn978-1-5090-2279-3
dc.identifier.issn1095-2055
dc.identifier.otherWOS:000389589500100
dc.identifier.urihttp://dx.doi.org/10.1109/ICCCN.2016.7568586
dc.identifier.urihttp://hdl.handle.net/10057/12827
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractRecently, large-scale spectrum measurements show that geo-location spectrum databases, as recommended by regulators (e.g., FCC, Ofcom, ECC) for TV white space (TVWS) discovery are notoriously inaccurate in Metropolitan areas because of inaccurate TV channel propagation models they adopted. To counter this challenge, we propose a cloud-based crowd-augmented spectrum mapping scheme. Our scheme aims to build accurate geo-location database in Metropolitan areas with high spatial resolution under minimum cost by jointly utilizing superior computing capacity of cloud servers, abundant spectrum sensing data from crowd of mobile white-spaces device (WSD) users and the well-established geo-statistical techniques. More specifically, our spectrum mapping scheme consists of three interdependent components (1) opportunistic mobile spectrum sensing, which exploits the high spatial diversity of mobile users along with low-cost embedded spectrum measuring solution to retrieve power spectrum density (PSD) information of the TV channels in a large Metropolitan region; (2) cloud-based geo-statistical spectrum mapping, which estimates PSD at unknown geographic locations by utilizing the abundant PSD data aggregated at the cloud server consisting of geo-statistical analysis and interpolation tools; (3) optimal spatial sampling, which further augments the accuracy of the spectrum map by selecting the optimal locations, at which additional spectrum sensing measurements are obtained to minimize the spectrum mapping error. To verify the performance of the proposed scheme, an experiment is conducted in our university campus. The experiment result shows that our proposed scheme can discover more spectrum opportunities than the information reported by commercially available geo-location spectrum databases.en_US
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2016 25th International Conference on Computer Communication and Networks (ICCCN);
dc.subjectMobile communicationen_US
dc.subjectSensorsen_US
dc.subjectTVen_US
dc.subjectDatabasesen_US
dc.subjectServersen_US
dc.subjectInterpolationen_US
dc.subjectUrban areasen_US
dc.titleTowards cloud-based crowd-augmented spectrum mapping for dynamic spectrum accessen_US
dc.typeConference paperen_US
dc.rights.holderCopyright © 2016, IEEEen_US


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